Improvement of Email And Twitter Classification Accuracy Based On Preprocessing Bayes Naive Classifier Optimization In Integrated Digital Assistant

Autor:	Aldo Erianda, Indri Rahmayuni
Jazyk:	angličtina
Rok vydání:	2017
Předmět:	bayes naive classifier preprocessing machine learning Computer software QA76.75-76.765
Zdroj:	JOIV: International Journal on Informatics Visualization, Vol 1, Iss 2, Pp 53-56 (2017)
Druh dokumentu:	article
ISSN:	2549-9610 2549-9904
DOI:	10.30630/joiv.1.2.21
Popis:	This research focuses on improving the accuracy of email and twitter classification. Spelling mistakes and lack of matches with bag of word causes the low accuracy in classifying. This research used naïve Bayes as a text classification algorithms. Text is divided into three categories: personal, work and family. To achieve maximum likelikehood value for the category, a better preprocessing techniques is needed. It is necessary for the process to normalize the preprocessing and search for words that correspond to classes in the bag of word. So that the text can be classified by category or has a higher precision accuracy.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/2120a420ade945bb904331ec9a722221 Zobrazit plný text záznamu View record in DOAJ